3 citations · 9 across the 12 of their papers we have counts for
12 papers
SPG: Sparse-Projected Guides with Sparse Autoencoders for Zero-Shot Anomaly Detection
Tomoyasu Nanaumi, Yukino Tsuzuki, Junichi Okubo +2
We study zero-shot anomaly detection and segmentation using frozen foundation model features, where all learnable parameters are trained only on a labeled auxiliary dataset and dep…
Disaster Anomaly Detector via Deeper FCDDs for Explainable Initial Responses
Takato Yasuno, Masahiro Okano, Junichiro Fujii
Extreme natural disasters can have devastating effects on both urban and rural areas. In any disaster event, an initial response is the key to rescue within 72 hours and prompt rec…
Wooden Sleeper Deterioration Detection for Rural Railway Prognostics Using Unsupervised Deeper FCDDs
Takato Yasuno, Masahiro Okano, Junichiro Fujii
Maintaining high standards for user safety during daily railway operations is crucial for railway managers. To aid in this endeavor, top- or side-view cameras and GPS positioning s…
One-class Damage Detector Using Deeper Fully-Convolutional Data Descriptions for Civil Application
Takato Yasuno, Masahiro Okano, Junichiro Fujii
Infrastructure managers must maintain high standards to ensure user satisfaction during the lifecycle of infrastructures. Surveillance cameras and visual inspections have enabled p…
MN-Pair Contrastive Damage Representation and Clustering for Prognostic Explanation
Takato Yasuno, Masahiro Okano, Junichiro Fujii
For infrastructure inspections, damage representation does not constantly match the predefined classes of damage grade, resulting in detailed clusters of unseen damages or more com…
River Surface Patch-wise Detector Using Mixture Augmentation for Scum-cover-index
Takato Yasuno, Junichiro Fujii, Masazumi Amakata
Urban rivers provide a water environment that influences residential living. River surface monitoring has become crucial for making decisions about where to prioritize cleaning and…
VAE-iForest: Auto-encoding Reconstruction and Isolation-based Anomalies Detecting Fallen Objects on Road Surface
Takato Yasuno, Junichiro Fujii, Riku Ogata +1
In road monitoring, it is an important issue to detect changes in the road surface at an early stage to prevent damage to third parties. The target of the falling object may be a f…
Flood Inflow Forecast Using L2-norm Ensemble Weighting Sea Surface Feature
Takato Yasuno, Masazumi Amakata, Junichiro Fujii +2
It is important to forecast dam inflow for flood damage mitigation. The hydrograph provides critical information such as the start time, peak level, and volume. Particularly, dam m…
One-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map
Takato Yasuno, Junichiro Fujii, Sakura Fukami
For steel product manufacturing in indoor factories, steel defect detection is important for quality control. For example, a steel sheet is extremely delicate, and must be accurate…
Road Surface Translation Under Snow-covered and Semantic Segmentation for Snow Hazard Index
Takato Yasuno, Junichiro Fujii, Hiroaki Sugawara +1
In 2020, there was a record heavy snowfall owing to climate change. In reality, 2,000 vehicles were stuck on the highway for three days. Because of the freezing of the road surface…
Snowy Night-to-Day Translator and Semantic Segmentation Label Similarity for Snow Hazard Indicator
Takato Yasuno, Hiroaki Sugawara, Junichiro Fujii +1
In 2021, Japan recorded more than three times as much snowfall as usual, so road user maybe come across dangerous situation. The poor visibility caused by snow triggers traffic acc…
Generative Damage Learning for Concrete Aging Detection using Auto-flight Images
Takato Yasuno, Akira Ishii, Junichiro Fujii +2
In order to monitor the state of large-scale infrastructures, image acquisition by autonomous flight drones is efficient for stable angle and high-quality images. Supervised learni…